# Parallect

> Use this tool when you need to streamline complex research tasks by aggregating insights from multiple AI providers into a single, cohesive report, saving time and effort in data analysis and synthesis. It solves problems of information overload and inconsistent findings by providing a unified output. Ideal for use cases requiring comprehensive and accurate research summaries, such as academic studies, market research, or strategic planning.

Canonical page: https://skillsregistry.net/skills/io-github-securecoders-parallect  
JSON: https://api.skillsregistry.net/v1/skills/io-github-securecoders-parallect

## Description

Fan out deep research across multiple AI providers, synthesize into one unified report.

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** search
- **Updated:** 2026-05-09

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/io.github.securecoders%2Fparallect)

## Use it

MCP endpoint published by the skill: `https://parallect.ai/api/mcp/mcp`

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "io-github-securecoders-parallect"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/io-github-securecoders-parallect` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/io-github-securecoders-parallect/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt